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Sparse Reasoning Intelligence & Quality

sriq-ai

Models in Library1
Datasets in Library0
Models on Hugging Face13
Followers4

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This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Image and text to text.

Reported licenses: apache-2.0. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Merged bf16 weights. Reasons in compressed Simplified Chinese and answers in the language it was asked in. No benchmarks were run for this release. Nothing here reports rows that reason in Chinese, verification rate, or looping against the base model. Evaluate it on your own workload before relying on it. - Training saw 2,940 of the dataset's 2,940 rows at 700 steps on an effective batch of 8, about 1.90 of one epoch. - Inherits the base model's limitations. Do not pass enablethinking=False: the template prefills an empty and the trace disappears. Wall clock and cost are measured by the agent from its own start to publish, so they cover the base-model download and the merge upload as well…

Open weights apache-2.0 9.7B parameters 262,144 tokens transformers
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